Rashmi Korlakai Vinayak

Rashmi Korlakai Vinayak is an Associate Professor in the Computer Science Department at Carnegie Mellon University, where she leads the TheSys research group and contributes to the Parallel Data Lab (PDL). Her research focuses on robustness and resource efficiency in data systems across storage, computation, and communication. She employs a multidisciplinary approach combining computer systems, information theory, and machine learning to develop next-generation data systems.

Research interests span:

• Fault tolerance and efficiency in storage systems
• High-performance caching architectures
• Machine learning systems optimization
• Coding theory applications in distributed systems

Recent publications demonstrate a strong emphasis on distributed computing optimization, GPU utilization, and novel algorithms for web caching and storage management. Her work consistently addresses scalability challenges in large-scale systems.

Awards include prestigious fellowships from Sloan Foundation and IEEE, with industry recognition from Meta, VMware, and Google. Current projects involve collaborations with NetApp, Facebook, Cisco, Intel, and Cloudera.

She advises PhD and Master's students working on systems optimization projects, and has developed industry-adopted solutions now integrated into platforms like Apache Hadoop and VMware.